{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.3.0\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据导入、分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 下载资源包时遇到了很多问题，由于网络原因数据包一直无法下载最后询问同学得到了，成果导入了数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "fashion_mnist = keras.datasets.fashion_mnist\n",
    "\n",
    "(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60000, 28, 28)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_images.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([9, 0, 0, ..., 3, 0, 5], dtype=uint8)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60000"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.imshow(train_images[0])\n",
    "plt.colorbar()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "for i in range(25):\n",
    "    plt.subplot(5,5,i+1)\n",
    "    plt.imshow(train_images[i],cmap=plt.cm.binary) \n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "    plt.grid(False)\n",
    "    plt.xlabel(train_labels[i])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat','Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "for i in range(25):\n",
    "    plt.subplot(5,5,i+1)\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "    plt.grid(False)\n",
    "    plt.imshow(train_images[i], cmap=plt.cm.binary)\n",
    "    plt.xlabel(class_names[train_labels[i]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TensorFlow and tf.keras\n",
    "import tensorflow as tf\n",
    "from tensorflow import keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = keras.Sequential([\n",
    "    keras.layers.Flatten(input_shape=(28, 28)),\n",
    "    keras.layers.Dense(256, activation='relu'),\n",
    "    keras.layers.Dense(10)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer='adam',\n",
    "              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "1875/1875 [==============================] - 2s 993us/step - loss: 3.6393 - accuracy: 0.7391\n",
      "Epoch 2/10\n",
      "1875/1875 [==============================] - 2s 939us/step - loss: 0.5654 - accuracy: 0.8015\n",
      "Epoch 3/10\n",
      "1875/1875 [==============================] - 2s 868us/step - loss: 0.5169 - accuracy: 0.8196\n",
      "Epoch 4/10\n",
      "1875/1875 [==============================] - 2s 946us/step - loss: 0.5041 - accuracy: 0.8287\n",
      "Epoch 5/10\n",
      "1875/1875 [==============================] - 2s 933us/step - loss: 0.4818 - accuracy: 0.8347\n",
      "Epoch 6/10\n",
      "1875/1875 [==============================] - 2s 862us/step - loss: 0.4704 - accuracy: 0.8403\n",
      "Epoch 7/10\n",
      "1875/1875 [==============================] - 2s 884us/step - loss: 0.4717 - accuracy: 0.8397\n",
      "Epoch 8/10\n",
      "1875/1875 [==============================] - 2s 911us/step - loss: 0.4643 - accuracy: 0.8405\n",
      "Epoch 9/10\n",
      "1875/1875 [==============================] - 2s 863us/step - loss: 0.4502 - accuracy: 0.8449\n",
      "Epoch 10/10\n",
      "1875/1875 [==============================] - 2s 871us/step - loss: 0.4547 - accuracy: 0.8448\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x1eaba97da48>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(train_images, train_labels, epochs=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "313/313 - 0s - loss: 0.5745 - accuracy: 0.8095\n",
      "\n",
      "Test accuracy: 0.809499979019165\n"
     ]
    }
   ],
   "source": [
    "test_loss, test_acc = model.evaluate(test_images,  test_labels, verbose=2)\n",
    "\n",
    "print('b\\nTest accuracy:', test_acc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "probability_model = tf.keras.Sequential([model, \n",
    "                                         tf.keras.layers.Softmax()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = probability_model.predict(test_images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_image(i, predictions_array, true_label, img):\n",
    "  predictions_array, true_label, img = predictions_array, true_label[i], img[i]\n",
    "  plt.grid(False)\n",
    "  plt.xticks([])\n",
    "  plt.yticks([])\n",
    "\n",
    "  plt.imshow(img, cmap=plt.cm.binary)\n",
    "\n",
    "  predicted_label = np.argmax(predictions_array)\n",
    "  if predicted_label == true_label:\n",
    "    color = 'blue'\n",
    "  else:\n",
    "    color = 'red'\n",
    "\n",
    "  plt.xlabel(\"{} {:2.0f}% ({})\".format(class_names[predicted_label],\n",
    "                                100*np.max(predictions_array),\n",
    "                                class_names[true_label]),\n",
    "                                color=color)\n",
    "\n",
    "def plot_value_array(i, predictions_array, true_label):\n",
    "  predictions_array, true_label = predictions_array, true_label[i]\n",
    "  plt.grid(False)\n",
    "  plt.xticks(range(10))\n",
    "  plt.yticks([])\n",
    "  thisplot = plt.bar(range(10), predictions_array, color=\"#777777\")\n",
    "  plt.ylim([0, 1])\n",
    "  predicted_label = np.argmax(predictions_array)\n",
    "\n",
    "  thisplot[predicted_label].set_color('red')\n",
    "  thisplot[true_label].set_color('blue')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_rows = 5\n",
    "num_cols = 3\n",
    "num_images = num_rows*num_cols\n",
    "plt.figure(figsize=(2*2*num_cols, 2*num_rows))\n",
    "for i in range(num_images):\n",
    "  plt.subplot(num_rows, 2*num_cols, 2*i+1)\n",
    "  plot_image(i, predictions[i], test_labels, test_images)\n",
    "  plt.subplot(num_rows, 2*num_cols, 2*i+2)\n",
    "  plot_value_array(i, predictions[i], test_labels)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
